Convergence: RAISE: Systems Approaches for Vulnerability Evaluation and Urban Resilience

无法评估和预测城市内极端天气状况的程度和影响是一个严重的脆弱性。 城市洪水来自于河流和小溪的泛滥，以及不透水的表面结构排水不足。 缺乏对洪水的邻里规模预测阻碍了社会和公共卫生干预工作。 空气质量和热岛/温度影响也存在类似的限制。该研究项目将联合收割机从自然，社会，数据和工程科学的角度来提高预测的天气模式，空气质量，洪水，社会和经济影响在邻里规模。 传感器安装和模型模拟将用于研究绿色基础设施的潜力，以减少洪水，缓和热浪，并改善当地和整个地区的空气质量。 综合降雨、地形、城市基础设施和不透水表面的模型目前还不可行或不可用。这个研究项目将使以前单独处理的水路由机制的整合，现在可以被认为是一个更大的更复杂的问题的一部分。 项目成果将直接用于芝加哥社区的脆弱性评估和基础设施设计。这一融合项目将促进新的多层次城市评估和预测能力;产生新的城市规模模拟天气、基础设施和人口脆弱性之间联系的能力;并展示这一新的系统级预测框架在适应性绿色基础设施设计中的应用。 该项目的主要组成部分包括：（1）安装和利用遥感和分布式传感来测量影响;（2）高分辨率基础设施/环境模型，阐明恶劣天气、城市基础设施和脆弱性之间的联系;（3）评估极端天气、基础设施和城市地形造成的共同社会和经济影响。 许多研究生和博士后将直接参与该项目。该项目将为地方管辖区提供脆弱性地图，并将鼓励政府和公共/私营部门就城市易受极端天气影响的脆弱性以及潜在的复原战略进行讨论。项目数据将通过芝加哥数据门户网站公开。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The inability to assess and predict the extent and impact of extreme weather conditions within cities is a critical vulnerability. Urban floods come from overflowing rivers and streams as well as insufficient drainage from impervious surface structures. The lack of neighborhood-scale forecasts for flooding hampers social and public health intervention efforts. Similar limitations exist for air quality and heat island/temperature impacts. This research project will combine perspectives from natural, social, data and engineering sciences to improve the prediction of weather patterns, air quality, flooding, and social and economic impacts at the neighborhood scale. Sensor installations and model simulations will be used to examine the potential for green infrastructure to reduce flooding, moderate heat waves, and improve air quality locally and across the region. Models that integrate across rainfall, topography, urban infrastructure and impervious surfaces are not currently viable or available. This research project will enable the integration of water routing mechanisms that were previous treated separately and can now be considered as portions of a larger more complex problem. Project results will be directly used for vulnerability assessment and infrastructure design in Chicago neighborhoods.This convergence project will catalyze new multi-level urban assessment and prediction capabilities; yield new capacity for city-scale simulations of links between weather, infrastructure, and population vulnerability; and demonstrate the application of this new systems-level prediction framework to adaptive green infrastructure design. The principle components of the project include (1) installation and utilization of remote and distributed sensing to measure impacts; (2) high-resolution infrastructure/environmental models that elucidate links between severe weather, urban infrastructure, and vulnerability; and (3) an assessment of co-occurring social and economic impacts as a result of extreme weather, infrastructure and urban topography. Many graduate students and postdocs will be directly engaged in the project. The project will contribute vulnerability maps to local jurisdictions and will encourage government and public/private discourse on urban vulnerability to extreme weather as well as potential resilience strategies. Project data will be publicly available through the Chicago Data Portal.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.